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Table 2 Description of the methods included in the benchmark

From: Improved model quality assessment using ProQ2

Method Description
ProQ2 (S) Support Vector Machine trained to predict S-score
ProQ (S) Neural network trained on structural features to predict LGscore [15] and S-score [9].
QMEAN (S) Potential of mean force, top-ranked single MQAP in CASP8 and CASP9 [18]
MetaMQAP (S) Neural network trained on the output from primary MQAPs [16]
Distill_NNPIF (S) Neural network trained on CA-CA interactions [25]
ConQuass (S) Correlates conservation and solvent accessibility, only global [10]
MULTICOM-CMFR (S) Top-ranked single MQAP in CASP8, only global [17].
QMEANclust (C) QMEAN-weighted GDT_TS averaging, top-ranked consensus method MQAP in CASP8 and CASP9 [23].
ProQ2+Pcons (C) Linear combination of ProQ2 and Pcons scores, 0.2ProQ2+0.8Pcons
  1. Description of the single-model methods and the reference consensus method included in the benchmark. The single methods (S) do not use any template or consensus information. Consensus and hybrid methods (C) are free to use any type of information. This method was originally called ProQres, but for clarity it will be referred to as ProQ both for global and local quality prediction. (S) single-model method (C) consensus method.